CN116580313B - Abnormal ship identification method and device based on digital twin and remote sensing - Google Patents
Abnormal ship identification method and device based on digital twin and remote sensing Download PDFInfo
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Abstract
The application provides a digital twin and remote sensing based abnormal ship identification method and device, which can realize the comparison and identification of abnormal ships in a large range in a sea-facing area by utilizing the ship constraint condition and satellite remote sensing data comparison and analysis. The screening work for abnormal ships can be advanced, and the abnormal ships can be found in advance at sea before an abnormal event occurs, so that the sufficient time is left for inspection. The abnormal ships are identified, the abnormal ships are subjected to grading early warning, the abnormal ships are focused and inspected according to the abnormal grade, and limited inspection force is reasonably distributed, so that the inspection accuracy is ensured, and the omission of inspection can be avoided. The workload of personnel is reduced, and the pertinence of examination is improved.
Description
Technical Field
The application relates to the technical field of satellite positioning, in particular to a digital twin and remote sensing-based abnormal ship identification method and device.
Background
The existing marine ship abnormal behavior identification is basically realized by carrying out track analysis on navigation data according to AIS data, GPS positioning data and the like, processing and analyzing an onshore video image, and comparing the navigation data with historical track data and route planning data to give warning to ships with obvious deviation. The method has poor recognition effect on some abnormal ships, and AIS data are not uploaded; secondly, the abnormal ships usually select the time period with bad sea conditions such as bad weather, early morning and the like to come out of the sea, so that the mode based on the on-shore video image analysis is also disabled; thirdly, the existing management is concentrated in the middle and later stages, no early prediction and early warning are performed, the inspection time is reserved for management staff, and the comparison is passive.
Therefore, how to provide an effective method for identifying abnormal behavior ships is a problem to be solved.
Disclosure of Invention
In order to solve the problems, the application provides a method and a device for identifying abnormal ships based on digital twin and remote sensing.
In a first aspect of an embodiment of the present application, there is provided a method for identifying abnormal vessels based on digital twin and remote sensing, the method comprising:
obtaining geographic information and sea state weather forecast data of a sea area to be identified, and constructing a digital twin base map with sea area weather information;
acquiring the ship information in the sea area to be identified;
screening the ship information according to preset constraint conditions, and marking the screened ship on the digital twin bottom map;
identifying the identified ship according to preset abnormal early warning conditions, wherein the abnormal early warning conditions comprise AIS data abnormal conditions, ship distance abnormal conditions, offshore weather abnormal conditions and abnormal conditions in a sea outlet period;
and identifying the abnormal ship according to the identified ship identified according to the abnormal early warning condition on the digital twin base map.
Optionally, the step of identifying the identified ship according to a preset abnormal early warning condition specifically includes:
acquiring satellite remote sensing data and AIS data of the identified ship;
identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
the satellite remote sensing data is subjected to unified space-time reference processing and satellite-ground coordinate conversion, and is compared with the ships in the digital twin base map, so that the ships which are displayed on the sea but not reporting AIS data in satellite remote sensing are identified;
identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
according to the comparison of the satellite remote sensing data and the AIS data, identifying that two or more vessels which are not associated with each other and have the distance lower than the driving safety distance are actively close to each other;
identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
identifying small ships which come out of the sea or go out of the sea against normal conditions under severe sea conditions according to the sea area meteorological information and the corresponding influence range;
identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
small vessels that are out of sea during an unusual out-of-sea period are identified.
Optionally, the step of identifying the abnormal ship according to the identified abnormal early warning condition on the digital twin base map specifically includes:
and identifying the abnormal ship according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions.
Optionally, the method further comprises:
and saving the ship information of the distinguished abnormal ship into a pre-established early warning database.
In a second aspect of the embodiment of the present application, there is provided an abnormal ship identification apparatus based on digital twin and remote sensing, the apparatus comprising:
the image generation unit is used for acquiring geographic information and sea state weather forecast data of the sea area to be identified and constructing a digital twin base map with sea area weather information;
the information acquisition unit is used for acquiring the ship information in the sea area to be identified;
the ship identification unit is used for screening ship information according to preset constraint conditions and identifying the screened ships on the digital twin base map;
the abnormal recognition unit is used for recognizing the marked ship according to preset abnormal early warning conditions, wherein the abnormal early warning conditions comprise AIS data abnormal conditions, ship distance abnormal conditions, offshore weather abnormal conditions and abnormal conditions of a sea outlet period;
and the abnormal identification unit is used for identifying the ship identified according to the abnormal early warning condition on the digital twin base map according to the identified condition.
Optionally, the anomaly identification unit is specifically configured to:
acquiring satellite remote sensing data and AIS data of the identified ship;
identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
the satellite remote sensing data is subjected to unified space-time reference processing and satellite-ground coordinate conversion, and is compared with the ships in the digital twin base map, so that the ships which are displayed on the sea but not reporting AIS data in satellite remote sensing are identified;
identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
according to the comparison of the satellite remote sensing data and the AIS data, identifying that two or more vessels which are not associated with each other and have the distance lower than the driving safety distance are actively close to each other;
identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
identifying small ships which come out of the sea or go out of the sea against normal conditions under severe sea conditions according to the sea area meteorological information and the corresponding influence range;
identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
small vessels that are out of sea during an unusual out-of-sea period are identified.
Optionally, the anomaly identification unit is specifically configured to:
and identifying the abnormal ship according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions.
Optionally, the apparatus further comprises:
and the information storage unit is used for storing the ship information of the distinguished abnormal ship into a pre-established early warning database.
A third aspect of an embodiment of the present application provides an electronic device, including:
one or more processors; a memory; one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method of the first aspect.
A fourth aspect of an embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium has program code stored therein, the program code being callable by a processor to perform the method according to the first aspect.
In summary, the application provides a digital twin and remote sensing based abnormal ship identification method and device, which can realize the comparison and identification of abnormal ships in a large range in a sea-facing area by utilizing the ship constraint condition and satellite remote sensing data comparison and analysis. The screening work for abnormal ships can be advanced, and the abnormal ships can be found in advance at sea before an abnormal event occurs, so that the sufficient time is left for inspection. The abnormal ships are identified, the abnormal ships are subjected to grading early warning, the abnormal ships are focused and inspected according to the abnormal grade, and limited inspection force is reasonably distributed, so that the inspection accuracy is ensured, and the omission of inspection can be avoided. The workload of personnel is reduced, and the pertinence of examination is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a method flow chart of an abnormal ship identification method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a digital twin base map with sea area weather information according to an embodiment of the present application;
FIG. 3 is a digital twin bottom map after screening for identification by vessel constraints in accordance with an embodiment of the present application;
FIG. 4 is a digital twin base map after screening identification according to AIS data exception conditions in an embodiment of the present application;
FIG. 5 is a digital twin bottom map after screening identification according to abnormal conditions of ship distance according to an embodiment of the present application;
FIG. 6 is a digital twin base map after screening for identification by offshore weather anomalies or time period anomalies in accordance with an embodiment of the present application;
FIG. 7 is a digital twin bottom map after hierarchical identification by abnormal watercraft grade in accordance with an embodiment of the present application;
FIG. 8 is a schematic diagram of the logic for implementing the abnormal watercraft identification method according to the embodiment of the application;
FIG. 9 is a functional block diagram of an abnormal ship identification apparatus according to an embodiment of the present application;
fig. 10 is a block diagram of an electronic device for performing an abnormal ship identification method according to an embodiment of the present application.
Fig. 11 is a block diagram of a computer-readable storage medium storing or carrying program code for implementing an abnormal ship identification method according to an embodiment of the present application.
Reference numerals:
an image generation unit 110; an information acquisition unit 120; a ship identification unit 130; an abnormality recognition unit 140; an abnormality identification unit 150; an information holding unit 160; an electronic device 300; a processor 310; a memory 320; a computer-readable storage medium 400; program code 410.
Detailed Description
The abnormal behavior identification of the marine vessels is realized by basically carrying out track analysis on navigation data according to AIS data, GPS positioning data and the like, processing and analyzing an onshore video image, comparing the processed and analyzed data with historical track data and route planning data, and giving a warning for the vessels with obvious deviation. The method has poor recognition effect on some abnormal ships, and AIS data are not uploaded; secondly, the abnormal ships usually select the time period with bad sea conditions such as bad weather, early morning and the like to come out of the sea, so that the mode based on the on-shore video image analysis is also disabled; thirdly, the existing management is concentrated in the middle and later stages, no early prediction and early warning are performed, the inspection time is reserved for management staff, and the comparison is passive.
Therefore, how to provide an effective method for identifying abnormal behavior ships is a problem to be solved.
In view of the above, the designer designs an abnormal ship identification method and device based on digital twin and remote sensing, and can realize the comparison and identification of abnormal ships in a large range in a sea-facing area by utilizing the ship constraint condition and satellite remote sensing data comparison and analysis. The screening work for abnormal ships can be advanced, and the abnormal ships can be found in advance at sea before an abnormal event occurs, so that the sufficient time is left for inspection. The abnormal ships are identified, the abnormal ships are subjected to grading early warning, the abnormal ships are focused and inspected according to the abnormal grade, and limited inspection force is reasonably distributed, so that the inspection accuracy is ensured, and the omission of inspection can be avoided. The workload of personnel is reduced, and the pertinence of examination is improved.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
In the description of the present application, it should be noted that, directions or positional relationships indicated by terms such as "top", "bottom", "inner", "outer", etc., are directions or positional relationships based on those shown in the drawings, or those that are conventionally put in use, are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like, are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
In the description of the present application, it should also be noted that, unless explicitly specified and limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
Referring to fig. 1, the method for identifying abnormal ships based on digital twin and remote sensing provided in this embodiment includes:
step S101, geographical information and sea state weather forecast data of a sea area to be identified are obtained, and a digital twin base map with sea area weather information is constructed.
Firstly, constructing a digital twin base map on the sea according to geographic information of a sea area to be identified, and then predicting the date, time period and sea area of severe weather by combining sea condition weather forecast data, and marking on the digital twin base map on the sea to form the digital twin base map with sea area weather information. The constructed digital twin base map with sea area weather information is shown in figure 2.
And step S102, acquiring the ship information in the sea area to be identified.
The ship information includes, in particular, the ship owner, the tonnage type, the use, the type, the time of sea going out, etc. of the ship.
And step S103, screening the ship information according to preset constraint conditions, and marking the screened ship on the digital twin base map.
As a preferred implementation manner of the present embodiment, the preset constraint condition is related to the ship information, and the screening of the ship from each dimension of the ship information is achieved through the setting of the constraint condition.
According to preset ship constraint conditions, such as tonnage range, application type, sea-going time and the like in ship information, ships meeting the constraint conditions are screened from an AIS database, and a specific case is shown in the following table:
the set constraint conditions are as follows: if the tonnage is less than or equal to 500 tons; the application type is offshore fishing, fishing and cultivation;
| ship number | Ship owner | Type of tonnage | Use of the same | Time of sea going out | Report and prepare information |
| XXX | Tension XX | 200 tons | Fishing device | XX day 7:30 | XXX |
| XXX | Plum XX | 150 tons | Fishing device | XX day 6:30 | XXX |
| XXX | Korean XX | Motorboat | Tour guide | XX day 7:00 | XXX |
| … | |||||
Based on the screening result, the digital twin base map is marked, and the specific marking condition is shown in fig. 3.
Step S104, identifying the identified ship according to preset abnormal early warning conditions, wherein the abnormal early warning conditions comprise AIS data abnormal conditions, ship distance abnormal conditions, offshore weather abnormal conditions and sea-out period abnormal conditions.
For the abnormal condition of the marine ship, a plurality of different specific scenes are corresponding, so that corresponding abnormal conditions are needed to be adopted for different scenes to judge and identify.
The specific identification method comprises the following steps:
acquiring satellite remote sensing data and AIS data of the identified ship;
for satellite remote sensing data, unified space-time reference processing and satellite-ground coordinate conversion are required.
Identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
and comparing the satellite remote sensing data with the ships in the digital twin base map through unified space-time reference processing and satellite-ground coordinate conversion, and identifying the ships with the satellite remote sensing display appearing on the sea but not reporting AIS data.
The AIS data abnormal conditions aim at the ships without reporting AIS data, identify the ships which appear on the sea without reporting AIS data by satellite remote sensing, and highlight and mark on a base map, which is a scene of one type of abnormal ships. The results after specific identification are shown in fig. 4.
Identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
and identifying the ships which are actively close to each other under two or more unassociated conditions and have a distance lower than the driving safety distance according to the comparison of the satellite remote sensing data and the AIS data.
The abnormal condition of the ship distance aims at the condition that the ship is abnormally close, and when the abnormal condition is identified, the association condition mainly refers to specific information with a certain association relation in ship information, such as ships of which the ship owners do not belong to the same person or the same company, ships with different or irrelevant business, ships with large tonnage difference and the like. The number of unassociated conditions in the recognition may be set in advance, or may be two or more. The categories of unassociated conditions may be specified in several ship information dimensions, or may be arbitrary ship information dimensions.
For judging whether the distance exceeds the driving safety distance, the distance can be adjusted by setting different driving safety distance values. When the identification is carried out, two dimensions are needed to be judged, one is whether two or more than two uncorrelated conditions exist on the approaching ships, the other is whether the distance between the ships is lower than the driving safety distance, and if the distances are all met, the scene of one abnormal ship is corresponding. The result after specific identification is shown in fig. 5.
Identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
and identifying the small-sized ship which goes out of the sea or goes out of the sea against the normal theory under the severe sea condition according to the sea area meteorological information and the corresponding influence range.
The marine weather abnormal condition is aimed at the condition that the ship is forced out of the sea under unnecessary conditions. On the digital twin bottom map, there are displays of severe weather occurrences such as fog, high waves, etc. And finding that the ship appears in the range according to the range of severe weather of weather forecast, and considering that the identification condition is met. For the identification against the usual sea-out, corresponding identification conditions may be preset, such as that the ship configuration does not reach the sea-out requirement, that the ship use does not correspond to the sea-out position, that the disaster weather is not compliant with recall management or that the dangerous sea area is evacuated without a prescribed time limit. The above situation also corresponds to a scenario of an abnormal class of vessels.
When judging the scene, the method mainly aims at small ships, can preset the tonnage limit of the small ships for the definition of the small ships, and considers the ships which do not reach the tonnage as the small ships.
For the specific situations involved in sea going out in severe sea conditions or going out of normal sea going out, the identification and marking is performed for the ship satisfying one of the conditions. The results after specific identification are shown in fig. 6.
Identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
small vessels that are out of sea during an unusual out-of-sea period are identified.
The abnormal condition of the out-of-sea period corresponds to the identification of small vessels out-of-sea during an irregular out-of-sea period, such as an early morning period, which also corresponds to the scenario of a class of abnormal vessels. The specific corresponding time of the irregular sea-going period may be preset or associated with the time when bad weather occurs.
The definition for a small ship is the same as described above. The results after specific identification are shown in fig. 6.
And step 105, identifying the abnormal ship according to the identified ship according to the abnormal early warning condition on the digital twin base map.
In order to facilitate the user to check the abnormal ship condition, the abnormal ship is identified according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions. Aiming at the scenes of the four types of abnormal ships, respectively identifying the abnormal ships, respectively giving grading early warning according to the conditions of one type, two types, three types or four types, and marking the abnormal ships on an offshore digital twin base map by using marks with different colors (settable). The results after specific identification are shown in fig. 7. For viewing, the detailed information (such as ship number, ship owner, use, stock etc.) of the displayable ship can be clicked.
Based on the above, the logic for implementing the abnormal ship identification method according to the embodiment of the present application is shown in fig. 8.
As a preferred implementation manner, the abnormal ship identification method provided in this embodiment further includes: and saving the ship information of the distinguished abnormal ship into a pre-established early warning database.
And the data accumulation is carried out by storing the ship information of the abnormal ship with the distinguished history, so that the subsequent analysis and the subsequent call are facilitated. The user can send out early warning information in advance for ships which may be abnormal by calling the information in the early warning database.
In summary, the abnormal ship identification method provided in the present embodiment has the following advantages:
the range is large: the application generally analyzes abnormal ships according to AIS data route tracks and videos, has a small range, and can realize the comparison and extraction of abnormal ships in a large range in a sea-facing area by utilizing the ship constraint condition and remote sensing comparison analysis.
The examination region is advanced: the present application generally inspects ships on wharfs and banks, has the advantages of short time and great difficulty, and the present application advances the screening work of abnormal ships, and before an abnormal event occurs, the abnormal ships are found in advance on the sea, so that sufficient time is left for inspection.
The pertinence is strong: the application greatly reduces the number range and the position of the area of abnormal ships after analysis, screening and comparison, reduces the workload of personnel and improves the inspection pertinence.
And (5) grading and checking according to the degree of abnormality and the degree of urgency: the abnormal ships are extracted, the abnormal ships are subjected to grading early warning, the abnormal ships are focused and inspected according to the abnormal grade, and limited inspection force is reasonably distributed, so that the inspection accuracy is ensured, and the omission of inspection can be avoided.
As shown in fig. 9, the abnormal ship identification device provided by the embodiment of the application comprises:
the image generating unit 110 is used for acquiring geographic information and sea state weather forecast data of a sea area to be identified and constructing a digital twin base map with sea area weather information;
an information acquisition unit 120 for acquiring ship information in the sea area to be identified;
the ship identification unit 130 is configured to screen ship information according to preset constraint conditions, and identify the screened ship on the digital twin base map;
the anomaly identification unit 140 is configured to identify the identified ship according to preset anomaly early warning conditions, where the anomaly early warning conditions include an AIS data anomaly condition, a ship distance anomaly condition, an offshore weather anomaly condition, and a sea-out period anomaly condition;
and the anomaly identification unit 150 is used for identifying the vessels identified according to the anomaly early warning conditions on the digital twin base map according to the identified conditions.
As a preferred implementation manner of this embodiment, the anomaly identification unit 140 is specifically configured to:
acquiring satellite remote sensing data and AIS data of the identified ship;
identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
the satellite remote sensing data is subjected to unified space-time reference processing and satellite-ground coordinate conversion, and is compared with the ships in the digital twin base map, so that the ships which are displayed on the sea but not reporting AIS data in satellite remote sensing are identified;
identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
according to the comparison of the satellite remote sensing data and the AIS data, identifying that two or more vessels which are not associated with each other and have the distance lower than the driving safety distance are actively close to each other;
identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
identifying small ships which come out of the sea or go out of the sea against normal conditions under severe sea conditions according to the sea area meteorological information and the corresponding influence range;
identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
small vessels that are out of sea during an unusual out-of-sea period are identified.
As a preferred implementation manner of this embodiment, the anomaly identification unit 150 is specifically configured to:
and identifying the abnormal ship according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions.
As a preferred implementation of this embodiment, the apparatus further includes:
an information holding unit 160 for holding the ship information of the distinguished abnormal ship in a pre-established pre-warning database.
The abnormal ship identification device provided by the embodiment of the application is used for realizing the abnormal ship identification method, so that the specific implementation manner is the same as that of the method, and the detailed description is omitted herein.
As shown in fig. 10, an embodiment of the present application provides a block diagram of an electronic device 300. The electronic device 300 may be a smart phone, tablet, electronic book, etc. capable of running an application program of the electronic device 300. The electronic device 300 of the present application may include one or more of the following components: a processor 310, a memory 320, and one or more applications, wherein the one or more applications may be stored in the memory 320 and configured to be executed by the one or more processors 310, the one or more applications configured to perform the method as described in the foregoing method embodiments.
Processor 310 may include one or more processing cores. The processor 310 utilizes various interfaces and lines to connect various portions of the overall electronic device 300, perform various functions of the electronic device 300, and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 320, and invoking data stored in the memory 320. Alternatively, the processor 310 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 310 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for being responsible for rendering and drawing of display content; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 310 and may be implemented solely by a single communication chip.
The Memory 320 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Memory 320 may be used to store instructions, programs, code sets, or instruction sets. The memory 320 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described below, etc. The storage data area may also store data created by the terminal in use (such as phonebook, audio-video data, chat-record data), etc.
As shown in fig. 11, an embodiment of the present application provides a block diagram of a computer-readable storage medium 400. The computer readable medium has stored therein a program code 410, said program code 410 being callable by a processor for performing the method described in the above method embodiments.
The computer readable storage medium 400 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer readable storage medium 400 comprises a non-volatile computer readable medium (non-transitory computer-readable storage medium). The computer readable storage medium 400 has storage space for program code 410 that performs any of the method steps described above. These program code 410 can be read from or written to one or more computer program products. Program code 410 may be compressed, for example, in a suitable form.
In summary, the application provides a method, a device, electronic equipment and a readable storage medium for identifying abnormal ships based on digital twin and remote sensing, which can realize the comparison and identification of abnormal ships in a large range in a sea-facing area by utilizing the comparison and analysis of ship constraint conditions and satellite remote sensing data. The screening work for abnormal ships can be advanced, and the abnormal ships can be found in advance at sea before an abnormal event occurs, so that the sufficient time is left for inspection. The abnormal ships are identified, the abnormal ships are subjected to grading early warning, the abnormal ships are focused and inspected according to the abnormal grade, and limited inspection force is reasonably distributed, so that the inspection accuracy is ensured, and the omission of inspection can be avoided. The workload of personnel is reduced, and the pertinence of examination is improved.
In the several embodiments disclosed herein, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Claims (8)
1. An abnormal ship identification method based on digital twin and remote sensing, which is characterized by comprising the following steps:
obtaining geographic information and sea state weather forecast data of a sea area to be identified, and constructing a digital twin base map with sea area weather information;
acquiring the ship information in the sea area to be identified;
screening the ship information according to preset constraint conditions, and marking the screened ship on the digital twin bottom map;
identifying the identified ship according to preset abnormal early warning conditions, wherein the abnormal early warning conditions comprise AIS data abnormal conditions, ship distance abnormal conditions, offshore weather abnormal conditions and abnormal conditions in a sea outlet period;
on the digital twin base map, identifying the ship identified according to the abnormal early warning condition, and identifying the abnormal ship according to the identified condition;
the identifying the identified ship according to the preset abnormal early warning condition comprises the following steps:
acquiring satellite remote sensing data and AIS data of the identified ship;
identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
the satellite remote sensing data is subjected to unified space-time reference processing and satellite-ground coordinate conversion, and is compared with the ships in the digital twin base map, so that the ships which are displayed on the sea but not reporting AIS data in satellite remote sensing are identified;
identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
according to the comparison of the satellite remote sensing data and the AIS data, identifying that two or more vessels which are not associated with each other and have the distance lower than the driving safety distance are actively close to each other;
identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
identifying small ships which come out of the sea or go out of the sea against normal conditions under severe sea conditions according to the sea area meteorological information and the corresponding influence range;
identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
identifying a small vessel that is out of sea during an irregular out-of-sea period;
the association condition refers to specific information with a certain association relation in ship information, the association condition comprises ship owners of ships, service of the ships and tonnage of the ships, and the unassociated condition comprises ships of which the ship owners do not belong to the same person or the same company, ships of which the service is different or irrelevant, and ships of which the tonnage difference reaches a certain value;
according to the comparison of satellite remote sensing data and AIS data, the ship which is actively close to two or more unassociated conditions and has a distance lower than the driving safety distance is identified, and the method specifically comprises the following steps:
when the identification is carried out, two dimensions are judged, one is whether two or more than two irrelevant conditions exist on the approaching ships, the other is whether the distance between the ships is lower than the driving safety distance, and if the distances are met, the scenes of one type of abnormal ships are corresponding.
2. The method for identifying abnormal vessels according to claim 1, wherein the step of identifying abnormal vessels according to the identified abnormal pre-warning condition on the digital twin bottom map comprises the steps of:
and identifying the abnormal ship according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions.
3. The abnormal ship identification method of claim 1, further comprising:
and saving the ship information of the distinguished abnormal ship into a pre-established early warning database.
4. An abnormal ship identification device based on digital twinning and remote sensing, characterized in that the device comprises:
the image generation unit is used for acquiring geographic information and sea state weather forecast data of the sea area to be identified and constructing a digital twin base map with sea area weather information;
the information acquisition unit is used for acquiring the ship information in the sea area to be identified;
the ship identification unit is used for screening ship information according to preset constraint conditions and identifying the screened ships on the digital twin base map;
the abnormal recognition unit is used for recognizing the marked ship according to preset abnormal early warning conditions, wherein the abnormal early warning conditions comprise AIS data abnormal conditions, ship distance abnormal conditions, offshore weather abnormal conditions and abnormal conditions of a sea outlet period;
the abnormal identification unit is used for identifying the ship identified according to the abnormal early warning condition on the digital twin base map according to the identified condition;
the abnormality identification unit is specifically configured to:
acquiring satellite remote sensing data and AIS data of the identified ship;
identifying the identified ship through the AIS data abnormal condition, wherein the specific mode is as follows:
the satellite remote sensing data is subjected to unified space-time reference processing and satellite-ground coordinate conversion, and is compared with the ships in the digital twin base map, so that the ships which are displayed on the sea but not reporting AIS data in satellite remote sensing are identified;
identifying the identified ship through the ship distance abnormal condition, wherein the specific mode is as follows:
according to the comparison of the satellite remote sensing data and the AIS data, identifying that two or more vessels which are not associated with each other and have the distance lower than the driving safety distance are actively close to each other;
identifying the identified ship through the marine weather abnormal condition, wherein the specific mode is as follows:
identifying small ships which come out of the sea or go out of the sea against normal conditions under severe sea conditions according to the sea area meteorological information and the corresponding influence range;
identifying the identified ship through the abnormal conditions of the sea-going period, wherein the specific mode is as follows:
identifying a small vessel that is out of sea during an irregular out-of-sea period;
the association condition refers to specific information with a certain association relation in ship information, the association condition comprises ship owners of ships, service of the ships and tonnage of the ships, and the unassociated condition comprises ships of which the ship owners do not belong to the same person or the same company, ships of which the service is different or irrelevant, and ships of which the tonnage difference reaches a certain value;
according to the comparison of satellite remote sensing data and AIS data, the ship which is actively close to two or more unassociated conditions and has a distance lower than the driving safety distance is identified, and the method specifically comprises the following steps:
when the identification is carried out, two dimensions are judged, one is whether two or more than two irrelevant conditions exist on the approaching ships, the other is whether the distance between the ships is lower than the driving safety distance, and if the distances are met, the scenes of one type of abnormal ships are corresponding.
5. The abnormal ship identification apparatus according to claim 4, wherein said abnormal identification unit is specifically configured to:
and identifying the abnormal ship according to different grade identifications according to the matching quantity of the ship and different conditions in the abnormal early warning conditions.
6. The abnormal ship identification apparatus of claim 4, wherein said apparatus further comprises:
and the information storage unit is used for storing the ship information of the distinguished abnormal ship into a pre-established early warning database.
7. An electronic device, comprising:
one or more processors;
a memory;
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method of any of claims 1-3.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a program code, which is callable by a processor for performing the method according to any one of claims 1-3.
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